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BREAKING: Inside The ElevenLabs Summit The future of voice-first interfaces. CEO, Mati Staniszewski (@matiii) Head of Growth, Luke Harries (Luke Harries) Series A Lead, Bryan Kim (Bryan Kim) of a16z Klarna CEO, Sebastian Siemiatkowski (Sebastian Siemiatkowski) AIUC CEO, Rune Kvist (Rune Kvist) Founded in just 2022, has scaled to...

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Molly O’Shea

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143,008 görüntüleme • 6 ay önce •via X (Twitter)

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Why ElevenLabs chose to insure their ai voice agents with AIUC (Artificial Intelligence Underwriting Company): " We had a major announcement that we're going to be the first company to insure voice agents. If you're an enterprise, you can actually pay for insurance & if it goes out of bounds, something goes wrong, then you can make sure that you're covered." What's your hottest take on ai agents? "For most businesses, they're actually really risky & so they can go off script, they can say really bad things. You're maybe giving them tool use. And they're able to do refunds on your behalf. And so that's why we're really excited to announce the first insurable voice agents, where we've actually defined standard & a pathway around guardrails & audits so that you as a company, you can get an insurance product, which covers you to enable you to go to production at scale." Luke Harries (Luke Harries) Head of Growth Rune Kvist (Rune Kvist), CEO of AIUC, was the first product & GTM hire at Anthropic. Now he’s building the “confidence infrastructure” for the AGI era — combining standards (AIUC-1), audits, & insurance to de-risk AI deployments.
0:49

Why ElevenLabs chose to insure their ai voice agents with AIUC (Artificial Intelligence Underwriting Company): " We had a major announcement that we're going to be the first company to insure voice agents. If you're an enterprise, you can actually pay for insurance & if it goes out of bounds, something goes wrong, then you can make sure that you're covered." What's your hottest take on ai agents? "For most businesses, they're actually really risky & so they can go off script, they can say really bad things. You're maybe giving them tool use. And they're able to do refunds on your behalf. And so that's why we're really excited to announce the first insurable voice agents, where we've actually defined standard & a pathway around guardrails & audits so that you as a company, you can get an insurance product, which covers you to enable you to go to production at scale." Luke Harries (Luke Harries) Head of Growth Rune Kvist (Rune Kvist), CEO of AIUC, was the first product & GTM hire at Anthropic. Now he’s building the “confidence infrastructure” for the AGI era — combining standards (AIUC-1), audits, & insurance to de-risk AI deployments.

Molly O’Shea

30,368 görüntüleme • 6 ay önce

Learn to build conversational AI voice agents in "Building AI Voice Agents for Production", created in collaboration with LiveKit and RealAvatar, and taught by dsa (Co-founder & CEO of LiveKit), Shayne (Developer Advocate, LiveKit), and Nedelina Teneva (Head of AI at RealAvatar, an AI Fund portfolio company). Voice agents combine speech and reasoning capabilities to enable real-time conversations. They're already being used to support customer service, to improve accessibility in healthcare, for entertainment applications, and for talk therapy. In this course, you’ll learn to build voice agents that listen, reason, and respond naturally. You’ll follow the architecture used to create the "AI Andrew" Avatar, a collaborative project between and RealAvatar that responds to users in what sounds like my voice. You’ll build a voice agent from scratch and deploy it to the cloud, enabling support for many simultaneous users. What you’ll learn: - Understand the fundamentals of voice agents, including key components like speech-to-text (STT), text-to-speech (TTS), and LLMs, and how latency is introduced at each layer. - Explore voice agent architectures and the trade-offs between modular pipelines and speech-to-speech APIs. - Explore how platforms like LiveKit mitigate latency issues with optimized networking infrastructure and low-latency communication protocols. - Learn how to connect client devices to voice agents using WebRTC—and why it outperforms HTTP and WebSocket for low-latency audio streaming. - Incorporate voice activity detection (VAD), end-of-turn detection, and context management to detect turns, handle interruptions, and manage conversational flow. - Understand the trade-offs between latency, quality, and cost in an example in which you build a voice agent and change its voice. - Equip your agent with metrics to measure latency at each stage of the voice pipeline and learn the key levers you can pull to make your agent faster and more responsive. The voice agents built in this course also incorporate voice technology from , a supporting contributor to the project. By the end of this course, you'll have learned the components of an AI voice agent pipeline, combined them into a system with low-latency communication, and deployed them on cloud infrastructure so it scales to many users. I’m looking forward to seeing what voice agents you build from this course! Please sign up here:
2:41

Learn to build conversational AI voice agents in "Building AI Voice Agents for Production", created in collaboration with LiveKit and RealAvatar, and taught by dsa (Co-founder & CEO of LiveKit), Shayne (Developer Advocate, LiveKit), and Nedelina Teneva (Head of AI at RealAvatar, an AI Fund portfolio company). Voice agents combine speech and reasoning capabilities to enable real-time conversations. They're already being used to support customer service, to improve accessibility in healthcare, for entertainment applications, and for talk therapy. In this course, you’ll learn to build voice agents that listen, reason, and respond naturally. You’ll follow the architecture used to create the "AI Andrew" Avatar, a collaborative project between and RealAvatar that responds to users in what sounds like my voice. You’ll build a voice agent from scratch and deploy it to the cloud, enabling support for many simultaneous users. What you’ll learn: - Understand the fundamentals of voice agents, including key components like speech-to-text (STT), text-to-speech (TTS), and LLMs, and how latency is introduced at each layer. - Explore voice agent architectures and the trade-offs between modular pipelines and speech-to-speech APIs. - Explore how platforms like LiveKit mitigate latency issues with optimized networking infrastructure and low-latency communication protocols. - Learn how to connect client devices to voice agents using WebRTC—and why it outperforms HTTP and WebSocket for low-latency audio streaming. - Incorporate voice activity detection (VAD), end-of-turn detection, and context management to detect turns, handle interruptions, and manage conversational flow. - Understand the trade-offs between latency, quality, and cost in an example in which you build a voice agent and change its voice. - Equip your agent with metrics to measure latency at each stage of the voice pipeline and learn the key levers you can pull to make your agent faster and more responsive. The voice agents built in this course also incorporate voice technology from , a supporting contributor to the project. By the end of this course, you'll have learned the components of an AI voice agent pipeline, combined them into a system with low-latency communication, and deployed them on cloud infrastructure so it scales to many users. I’m looking forward to seeing what voice agents you build from this course! Please sign up here:

Andrew Ng

87,711 görüntüleme • 1 yıl önce

Introducing Lightning V3 - it beats every model we tested against. ElevenLabs, Cartesia, OpenAI. Lightning sets a new SOTA with V3 in conversational text-to-speech. → Highest MOS score for conversational TTS at 3.9 → ~76% win rate vs gpt-4o-mini-tts on naturalness → 15 languages with mid-sentence code-switching → Built from scratch for voice agents, not read-aloud Every TTS model sounds clean in a demo. You type a sentence and you get beautiful audio. Voice agents don't work that way. They stream. They're generating audio in real-time chunks with half the context missing. That's where everything breaks. A great reading voice and a great conversational voice are fundamentally different things. A conversational voice has to sound like it's thinking - with the pauses, the rhythm shifts, the reactions. It has to handle the way real people actually talk, including switching languages mid-sentence. That's what V3 does. V3.1 also ships voice cloning. 5 to 15 seconds of audio, no fine-tuning, production-grade clone across 15 languages. Blog link in the comments.
1:33

Introducing Lightning V3 - it beats every model we tested against. ElevenLabs, Cartesia, OpenAI. Lightning sets a new SOTA with V3 in conversational text-to-speech. → Highest MOS score for conversational TTS at 3.9 → ~76% win rate vs gpt-4o-mini-tts on naturalness → 15 languages with mid-sentence code-switching → Built from scratch for voice agents, not read-aloud Every TTS model sounds clean in a demo. You type a sentence and you get beautiful audio. Voice agents don't work that way. They stream. They're generating audio in real-time chunks with half the context missing. That's where everything breaks. A great reading voice and a great conversational voice are fundamentally different things. A conversational voice has to sound like it's thinking - with the pauses, the rhythm shifts, the reactions. It has to handle the way real people actually talk, including switching languages mid-sentence. That's what V3 does. V3.1 also ships voice cloning. 5 to 15 seconds of audio, no fine-tuning, production-grade clone across 15 languages. Blog link in the comments.

Sudarshan Kamath

71,298 görüntüleme • 5 ay önce

Today Reactor is coming out of stealth. We’ve raised $59M in Seed and Series A funding, led by Lightspeed, with participation from Amplify Partners, wndrco, Sky9 Capital, and FPV Ventures. Reactor is the platform for building in the World Model era: the infrastructure that lets developers build with them at global scale for the first time. Stream from a frontier World Model to your app, in real time, all in under 10 lines of code. World Models represent the next major shift in AI: pixels, audio and actions are generated on the fly, in real-time, in response to user inputs, and to the environment. Every time computing has made a shift from passive to interactive, entire industries appeared that didn't exist before. We're standing in front of such moment again. Over the last 6 months, we’ve assembled an all-star team with alumni from Apple, Meta, Google, Luma AI, Netflix, and Replicate. We're already partnering with some of the biggest names and labs in the world, and hundreds of developers are already building on Reactor. The World Model era starts now.
1:52

Today Reactor is coming out of stealth. We’ve raised $59M in Seed and Series A funding, led by Lightspeed, with participation from Amplify Partners, wndrco, Sky9 Capital, and FPV Ventures. Reactor is the platform for building in the World Model era: the infrastructure that lets developers build with them at global scale for the first time. Stream from a frontier World Model to your app, in real time, all in under 10 lines of code. World Models represent the next major shift in AI: pixels, audio and actions are generated on the fly, in real-time, in response to user inputs, and to the environment. Every time computing has made a shift from passive to interactive, entire industries appeared that didn't exist before. We're standing in front of such moment again. Over the last 6 months, we’ve assembled an all-star team with alumni from Apple, Meta, Google, Luma AI, Netflix, and Replicate. We're already partnering with some of the biggest names and labs in the world, and hundreds of developers are already building on Reactor. The World Model era starts now.

reactor

12,737,146 görüntüleme • 3 ay önce

Today, we're thrilled to announce our $125M Series C funding round at a $1.5B valuation, led by Meritech Capital, marking our third successful raise in just 12 months! fal’s Generative Media Cloud now powers tens of thousands of applications, supporting over two million developers and more than 300 enterprise customers. From initial prototypes to fully scaled production, we've become the essential infrastructure enabling some of the most innovative and creative work in the industry. Over the past year alone, we've experienced extraordinary growth—averaging 40% month-over-month, consistently exceeding our own ambitious projections. Each month, hundreds of thousands of new developers and thousands of fresh applications join our platform, unlocking entirely new use cases previously thought impossible. With this latest round of funding, we're significantly scaling our engineering, support, sales, and marketing teams to keep pace with the accelerating demand and enthusiasm from our community. Our vision has always been clear: build a generative media platform that effortlessly creates dynamic, real-time content across video, audio, image, and 3D. Thanks to our incredible team, dedicated partners, and visionary customers, that's precisely what fal delivers today—empowering creativity at unprecedented scale.
1:34

Today, we're thrilled to announce our $125M Series C funding round at a $1.5B valuation, led by Meritech Capital, marking our third successful raise in just 12 months! fal’s Generative Media Cloud now powers tens of thousands of applications, supporting over two million developers and more than 300 enterprise customers. From initial prototypes to fully scaled production, we've become the essential infrastructure enabling some of the most innovative and creative work in the industry. Over the past year alone, we've experienced extraordinary growth—averaging 40% month-over-month, consistently exceeding our own ambitious projections. Each month, hundreds of thousands of new developers and thousands of fresh applications join our platform, unlocking entirely new use cases previously thought impossible. With this latest round of funding, we're significantly scaling our engineering, support, sales, and marketing teams to keep pace with the accelerating demand and enthusiasm from our community. Our vision has always been clear: build a generative media platform that effortlessly creates dynamic, real-time content across video, audio, image, and 3D. Thanks to our incredible team, dedicated partners, and visionary customers, that's precisely what fal delivers today—empowering creativity at unprecedented scale.

fal

1,451,147 görüntüleme • 1 yıl önce

Today we're announcing $280M in Series B funding at a $2B valuation, led by our long-time investor and partner, Menlo Ventures. When we announced our Series A last May, most conversations I had about voice began with someone explaining why they doubted it. I don't have those conversations anymore. People tell me instead how much time they save talking instead of typing and what they want us to build next. In a little over a year, voice has gone from something people were questioning to something they rely on, and it happened faster than we expected. That shift is why we've raised a new round of funding. This funding represents a deeper investment in our products, lab, models, and our team. Alongside the funding, we're announcing a preview of our first proprietary speech model, Canto. Canto is a 2B parameter speech model trained for the places people actually talk: loud rooms, windy streets, a toddler in the background, a second language mixed into the first. Models like this will change how we all interact with devices, and Canto is the first in a rapid line of them. Each one will be larger and more capable than the last, and each should improve Flow's dictation in a way you can feel the day it ships. Larger speech models also open the door to the vision we dreamed up 5 years ago: using your voice as the primary way you interact with devices. That still has to be invented. A voice interface people rely on all day, in every app, doesn't exist anywhere yet. It's time for that to change. To Sahaj Garg, our team, and every person who gave Wispr Flow a chance - this one's for you.
1:00

Today we're announcing $280M in Series B funding at a $2B valuation, led by our long-time investor and partner, Menlo Ventures. When we announced our Series A last May, most conversations I had about voice began with someone explaining why they doubted it. I don't have those conversations anymore. People tell me instead how much time they save talking instead of typing and what they want us to build next. In a little over a year, voice has gone from something people were questioning to something they rely on, and it happened faster than we expected. That shift is why we've raised a new round of funding. This funding represents a deeper investment in our products, lab, models, and our team. Alongside the funding, we're announcing a preview of our first proprietary speech model, Canto. Canto is a 2B parameter speech model trained for the places people actually talk: loud rooms, windy streets, a toddler in the background, a second language mixed into the first. Models like this will change how we all interact with devices, and Canto is the first in a rapid line of them. Each one will be larger and more capable than the last, and each should improve Flow's dictation in a way you can feel the day it ships. Larger speech models also open the door to the vision we dreamed up 5 years ago: using your voice as the primary way you interact with devices. That still has to be invented. A voice interface people rely on all day, in every app, doesn't exist anywhere yet. It's time for that to change. To Sahaj Garg, our team, and every person who gave Wispr Flow a chance - this one's for you.

Tanay Kothari

611,245 görüntüleme • 15 gün önce

We’re officially a YOUnicorn! 🦄 Excited to share that You.com just raised $100M Series C at a $1.5B valuation, led by Cox Enterprises. We’ve been heads down building the search infrastructure for the AI and agent future. Soon there will be more AI agents using the web than humans, but today's search wasn't built for this. Agents need deep, contextual information from both public web and internal private data to make real decisions. Our web search API delivers the most up-to-date, accurate, and fastest search results for LLMs and agents. Real benchmarks show we consistently outperform the competition on accuracy and speed while staying cost-effective. Today, we’re answering over 1 billion queries every month across enterprises like DuckDuckGo, Windsurf, Harvey, and many others. There is no other startup of recent years at this scale. Grateful to our wonderful employees, customers, partners, and investors who believe in our vision. The agentic era is here - let's build it together. Try our LLM search APIs.
2:25

We’re officially a YOUnicorn! 🦄 Excited to share that You.com just raised $100M Series C at a $1.5B valuation, led by Cox Enterprises. We’ve been heads down building the search infrastructure for the AI and agent future. Soon there will be more AI agents using the web than humans, but today's search wasn't built for this. Agents need deep, contextual information from both public web and internal private data to make real decisions. Our web search API delivers the most up-to-date, accurate, and fastest search results for LLMs and agents. Real benchmarks show we consistently outperform the competition on accuracy and speed while staying cost-effective. Today, we’re answering over 1 billion queries every month across enterprises like DuckDuckGo, Windsurf, Harvey, and many others. There is no other startup of recent years at this scale. Grateful to our wonderful employees, customers, partners, and investors who believe in our vision. The agentic era is here - let's build it together. Try our LLM search APIs.

Richard Socher

63,660 görüntüleme • 1 yıl önce

Today we’re announcing our $13M Seed round, led by Insight Partners with support from a16z a16z speedrun 🧊, Begin Capital, and Zero Prime VC. Over the past year, monthly revenue has grown 40x and we’ve integrated more than 400K models, establishing Runware as an essential service for AI teams that need price, performance, and reliability at scale. Our unified API now powers 100K+ developers daily. Serves 250M+ end users. And supports major enterprises, including Quora, OpenArt, NightCafe Studio, and Higgsfield AI 🧩. This funding allows us to expand our state-of-the-art model library with day-zero releases, move into new modalities like audio and LLMs, and invest heavily in R&D, documentation, and UI/UX to deliver the best developer experience in the industry. If you’re ready to see what Runware can do in production, reach out and we’ll set you up with free credits to get started. Pay less, build more.
0:28

Today we’re announcing our $13M Seed round, led by Insight Partners with support from a16z a16z speedrun 🧊, Begin Capital, and Zero Prime VC. Over the past year, monthly revenue has grown 40x and we’ve integrated more than 400K models, establishing Runware as an essential service for AI teams that need price, performance, and reliability at scale. Our unified API now powers 100K+ developers daily. Serves 250M+ end users. And supports major enterprises, including Quora, OpenArt, NightCafe Studio, and Higgsfield AI 🧩. This funding allows us to expand our state-of-the-art model library with day-zero releases, move into new modalities like audio and LLMs, and invest heavily in R&D, documentation, and UI/UX to deliver the best developer experience in the industry. If you’re ready to see what Runware can do in production, reach out and we’ll set you up with free credits to get started. Pay less, build more.

Runware

41,312 görüntüleme • 11 ay önce

We’re thrilled to share that Outset has raised $17M in Series A funding, led by 8VC to help companies better understand their customers. When michael hess and I founded Outset, we set out to solve a critical problem: truly understanding your customer is painfully slow, expensive, and at times, impossible. It shouldn’t be. We believed AI could change this by focusing on the human side of AI. So we built the world’s first AI-interviewer. An AI agent that asked questions, listened, and learned from real humans. By removing the barriers of traditional research and allowing companies to have deeper conversations with more customers more quickly, we could help teams infuse their products with genuine human understanding at a speed and scale previously impossible. So what was the moment we knew we were onto something? When WeightWatchers ran that first pilot back in early 2023. Participants shared incredible amounts of depth, all with the world’s first AI-interviewer. We got a call the next day from their head of research: "You built a thing. We want that thing. How do I pay you for it?" That validation has turned into explosive growth. We've doubled our revenue in just the last 4 months alone, with >50 enterprise customers like Nestlé, Microsoft, and WeightWatchers trusting us to unlock deeper customer insights. All of this built on the backs of a truly special early team with 0 employee turnover. This funding round was led by 8VC, with participation from an incredible group, including: Future Back Ventures by Bain & Company, Y Combinator / Garry Tan, Adverb Ventures /April Underwood / Jessica Verrilli ), Alt Capital / Jack Altman , Rebel Fund, Genius Ventures, Ritual Capital, and many more. So what's next? We're scaling our engineering and go-to-market teams to build the world's most powerful agentic customer research platform. All focused on one mission: helping companies better understand humans. To our customers, investors, and team - thank you for believing in this vision. Now check out the video to see Outset in action, testing the video itself with real people!
2:12

We’re thrilled to share that Outset has raised $17M in Series A funding, led by 8VC to help companies better understand their customers. When michael hess and I founded Outset, we set out to solve a critical problem: truly understanding your customer is painfully slow, expensive, and at times, impossible. It shouldn’t be. We believed AI could change this by focusing on the human side of AI. So we built the world’s first AI-interviewer. An AI agent that asked questions, listened, and learned from real humans. By removing the barriers of traditional research and allowing companies to have deeper conversations with more customers more quickly, we could help teams infuse their products with genuine human understanding at a speed and scale previously impossible. So what was the moment we knew we were onto something? When WeightWatchers ran that first pilot back in early 2023. Participants shared incredible amounts of depth, all with the world’s first AI-interviewer. We got a call the next day from their head of research: "You built a thing. We want that thing. How do I pay you for it?" That validation has turned into explosive growth. We've doubled our revenue in just the last 4 months alone, with >50 enterprise customers like Nestlé, Microsoft, and WeightWatchers trusting us to unlock deeper customer insights. All of this built on the backs of a truly special early team with 0 employee turnover. This funding round was led by 8VC, with participation from an incredible group, including: Future Back Ventures by Bain & Company, Y Combinator / Garry Tan, Adverb Ventures /April Underwood / Jessica Verrilli ), Alt Capital / Jack Altman , Rebel Fund, Genius Ventures, Ritual Capital, and many more. So what's next? We're scaling our engineering and go-to-market teams to build the world's most powerful agentic customer research platform. All focused on one mission: helping companies better understand humans. To our customers, investors, and team - thank you for believing in this vision. Now check out the video to see Outset in action, testing the video itself with real people!

Aaron Cannon

34,386 görüntüleme • 1 yıl önce

The Incredible Deal Behind Darth Vader’s AI Voice AI is making iconic characters immortal and giving creators a brand new revenue stream @jason: “The estate of James Earl Jones, before he passed, did a deal with $DIS and he said, ‘Listen, for my family, I would like to license the Darth Vader voice for all time to Disney.’ They gave him some incredible deal, and then they were left with, ‘Well, how do we actually do this? Do we get a voice impersonator?’ But instead they went to you.” ElevenLabs CEO Mati Staniszewski: “The big use case, a completely new experience, was in the gaming space where Fortnite launched Darth Vader, which people and players could interact with, live in partnership with the estate and in partnership with Disney. So every player, after reaching a certain stage, could have a Darth Vader interact and help you solve the missions. And we are seeing that kind of mode coming up more and more often of how you can effectively extend your likeness.” ------------------------------ Thanks to our partners for making this possible! Airwallex is a leading global payments and financial platform for modern businesses, offering trusted solutions to manage everything from business accounts, payments, treasury, and spend management to embedded finance. Oracle powers AI at every scale—from frontier labs to enterprise production. Your data. Leading models. No lock-in. One platform, architected for AI. Built for business. Visit #OracleAIExperienceLive
0:52

The Incredible Deal Behind Darth Vader’s AI Voice AI is making iconic characters immortal and giving creators a brand new revenue stream @jason: “The estate of James Earl Jones, before he passed, did a deal with $DIS and he said, ‘Listen, for my family, I would like to license the Darth Vader voice for all time to Disney.’ They gave him some incredible deal, and then they were left with, ‘Well, how do we actually do this? Do we get a voice impersonator?’ But instead they went to you.” ElevenLabs CEO Mati Staniszewski: “The big use case, a completely new experience, was in the gaming space where Fortnite launched Darth Vader, which people and players could interact with, live in partnership with the estate and in partnership with Disney. So every player, after reaching a certain stage, could have a Darth Vader interact and help you solve the missions. And we are seeing that kind of mode coming up more and more often of how you can effectively extend your likeness.” ------------------------------ Thanks to our partners for making this possible! Airwallex is a leading global payments and financial platform for modern businesses, offering trusted solutions to manage everything from business accounts, payments, treasury, and spend management to embedded finance. Oracle powers AI at every scale—from frontier labs to enterprise production. Your data. Leading models. No lock-in. One platform, architected for AI. Built for business. Visit #OracleAIExperienceLive

The All-In Podcast

35,020 görüntüleme • 1 ay önce

Greg Brockman, President of OpenAI, said there is not enough compute in the world to satisfy AI demand, and OpenAI itself cannot launch products it has already built because it cannot find the infrastructure to run them (Save this). OpenAI is spending $50 billion on compute in 2026 alone and it still is not enough. That is the setup but here is the trade. Nebius is one of the most asymmetric infrastructure plays in public markets right now, and most people have never heard of it. Q1 2026 revenue came in at $399 million, up 684% year over year, with AI cloud revenue specifically growing 841% in a single quarter. The company entered 2026 with an exit ARR of $1.25 billion and is targeting $7 to $9 billion by year end, a number that would make it one of the fastest revenue ramps in the history of public infrastructure companies. The contracted backlog sits at $50 billion anchored by a $17.4 billion agreement with Microsoft through 2031 and a $27 billion five-year deal with Meta. They are decade-scale infrastructure commitments from the two largest enterprise AI spenders on earth, signed before the demand curve has even reached its steepest point. Nvidia took a direct equity stake in Nebius, one of only two neoclouds it has invested in alongside CoreWeave. That relationship is not just financial but rather means Nebius gets preferential access to GPU allocation at a moment when every lab and every hyperscaler is competing for the same constrained supply. Contracted power capacity now exceeds 3.5 gigawatts, with expansion plans targeting 5 to 6 GW by mid-2029. And power is the other binding constraint in AI infrastructure, you cannot build a data center without it and Nebius has already secured the capacity that competitors are still fighting to acquire. At full ramp, analysts project revenue in the $15 to $25 billion range by 2029, against a current market cap the contracted backlog alone already dwarfs. Come join Milk Road Pro and get our full Nebius deep-dive, the exact price levels we are watching, how we are sizing the position against the backlog and power capacity timeline, and our full AI thesis. link below!
1:00

Greg Brockman, President of OpenAI, said there is not enough compute in the world to satisfy AI demand, and OpenAI itself cannot launch products it has already built because it cannot find the infrastructure to run them (Save this). OpenAI is spending $50 billion on compute in 2026 alone and it still is not enough. That is the setup but here is the trade. Nebius is one of the most asymmetric infrastructure plays in public markets right now, and most people have never heard of it. Q1 2026 revenue came in at $399 million, up 684% year over year, with AI cloud revenue specifically growing 841% in a single quarter. The company entered 2026 with an exit ARR of $1.25 billion and is targeting $7 to $9 billion by year end, a number that would make it one of the fastest revenue ramps in the history of public infrastructure companies. The contracted backlog sits at $50 billion anchored by a $17.4 billion agreement with Microsoft through 2031 and a $27 billion five-year deal with Meta. They are decade-scale infrastructure commitments from the two largest enterprise AI spenders on earth, signed before the demand curve has even reached its steepest point. Nvidia took a direct equity stake in Nebius, one of only two neoclouds it has invested in alongside CoreWeave. That relationship is not just financial but rather means Nebius gets preferential access to GPU allocation at a moment when every lab and every hyperscaler is competing for the same constrained supply. Contracted power capacity now exceeds 3.5 gigawatts, with expansion plans targeting 5 to 6 GW by mid-2029. And power is the other binding constraint in AI infrastructure, you cannot build a data center without it and Nebius has already secured the capacity that competitors are still fighting to acquire. At full ramp, analysts project revenue in the $15 to $25 billion range by 2029, against a current market cap the contracted backlog alone already dwarfs. Come join Milk Road Pro and get our full Nebius deep-dive, the exact price levels we are watching, how we are sizing the position against the backlog and power capacity timeline, and our full AI thesis. link below!

Milk Road AI

14,578 görüntüleme • 2 ay önce

Excited to share that we’ve raised $300M in our Series B round, led by Radical Ventures, bringing our total funding to more than $450M, with leading technology companies joining as both customers and investors. We continue accelerating the path to AGI through our two core pillars: ultra-optimized infrastructure for AI workloads, and realtime world models built on top of it. Today, we’re also launching DOS (Decart Optimization Stack) 2.0 – our next-generation inference and training platform, delivering over 1,600 tokens per second for agentic inference and over 100 FPS for world models across major hardware platforms. Alongside DOS, we will launch new versions of our world models in the coming weeks: Lucy, for immersive realtime experiences, and Oasis, for physical AI. Grateful to our partners, customers, and backers across media & entertainment, Physical AI, chips, hyperscalers, and the broader AI ecosystem. Radical Ventures, Adobe, Alpha Partners, Amazon and Amazon Web Services, Atreides Management, LP, Benchmark, eBay, NVIDIA, Sequoia Capital, Toyota USA, @valorep, oren zeev; Andrej Karpathy, Michael Eisner, Yamauchi-No.10 Family Office, Moritz Baier-Lentz and more. We made a film for this moment with Decart CEO Dean Leitersdorf and Moritz Baier-Lentz - a look at the company, the technology, and what comes next.
7:30

Excited to share that we’ve raised $300M in our Series B round, led by Radical Ventures, bringing our total funding to more than $450M, with leading technology companies joining as both customers and investors. We continue accelerating the path to AGI through our two core pillars: ultra-optimized infrastructure for AI workloads, and realtime world models built on top of it. Today, we’re also launching DOS (Decart Optimization Stack) 2.0 – our next-generation inference and training platform, delivering over 1,600 tokens per second for agentic inference and over 100 FPS for world models across major hardware platforms. Alongside DOS, we will launch new versions of our world models in the coming weeks: Lucy, for immersive realtime experiences, and Oasis, for physical AI. Grateful to our partners, customers, and backers across media & entertainment, Physical AI, chips, hyperscalers, and the broader AI ecosystem. Radical Ventures, Adobe, Alpha Partners, Amazon and Amazon Web Services, Atreides Management, LP, Benchmark, eBay, NVIDIA, Sequoia Capital, Toyota USA, @valorep, oren zeev; Andrej Karpathy, Michael Eisner, Yamauchi-No.10 Family Office, Moritz Baier-Lentz and more. We made a film for this moment with Decart CEO Dean Leitersdorf and Moritz Baier-Lentz - a look at the company, the technology, and what comes next.

Decart

98,781 görüntüleme • 3 ay önce

WARP SPEED: EPISODE 2 - starring Sobhan Nejdad, COO of Bland Sobhan Nejad Great AI isn't about being functional - it's about being exceptional. Sobhan and Isaiah Granet built Bland into one of the fastest-growing voice AI platforms in the world, powering conversational experiences for companies like Samsara, Snapchat, and EvenUp. In this episode, he explains why most voice AI feels like "another IVR tree with an LLM under the hood" - and how Bland focuses on the experience layer instead. Instead of settling for functional but robotic AI, Bland focused on: - Building voice infrastructure from scratch when it didn't exist - Reducing latency from 7 seconds to under 1 second - Creating AI brand representatives (Personas) that customers actually want to talk to - Hiring scrappy hustlers with chips on their shoulders who care about winning - Building a culture of kindness and direct feedback In this conversation: (0:00) - From prior auth healthcare startup to building Bland during YC (01:05) - Building a voice AI platform from scratch - the infrastructure just didn't exist (02:20) - Personas: One AI brand representative per company (02:57) - Hiring philosophy: Scrappy people from "tier 2 schools" who hustle hard and care about winning (03:58) - "The most exciting thing is the quality of people we get to work with" (04:16) - Switching from Rippling: "Loading screens for 30 seconds, really frustrating" (04:28) - How Warp delivers: Intuitive UX, proactive support, “built for high growth rapid startups”
5:13

WARP SPEED: EPISODE 2 - starring Sobhan Nejdad, COO of Bland Sobhan Nejad Great AI isn't about being functional - it's about being exceptional. Sobhan and Isaiah Granet built Bland into one of the fastest-growing voice AI platforms in the world, powering conversational experiences for companies like Samsara, Snapchat, and EvenUp. In this episode, he explains why most voice AI feels like "another IVR tree with an LLM under the hood" - and how Bland focuses on the experience layer instead. Instead of settling for functional but robotic AI, Bland focused on: - Building voice infrastructure from scratch when it didn't exist - Reducing latency from 7 seconds to under 1 second - Creating AI brand representatives (Personas) that customers actually want to talk to - Hiring scrappy hustlers with chips on their shoulders who care about winning - Building a culture of kindness and direct feedback In this conversation: (0:00) - From prior auth healthcare startup to building Bland during YC (01:05) - Building a voice AI platform from scratch - the infrastructure just didn't exist (02:20) - Personas: One AI brand representative per company (02:57) - Hiring philosophy: Scrappy people from "tier 2 schools" who hustle hard and care about winning (03:58) - "The most exciting thing is the quality of people we get to work with" (04:16) - Switching from Rippling: "Loading screens for 30 seconds, really frustrating" (04:28) - How Warp delivers: Intuitive UX, proactive support, “built for high growth rapid startups”

Ayush S

51,330 görüntüleme • 9 ay önce

Today we’re announcing our $50M Series A! Over the last year, we’ve grown from a small group with a big idea into a platform powering AI for hundreds of millions of end users across image, video, audio, and more. Since Q3, we’ve grown revenue by 10x, placing Runware comfortably among the fastest growing companies in the world. 🚀 When Runware started, the mission was simple: build the fastest and most reliable multimodal inference platform on the planet and make it accessible to everyone. We built our own Sonic Inference Engine, our own GPU infrastructure, our own inference pods, and a set of optimizations that push the limits of what an AI provider can do at scale. 2026 will be the year we bring inference closer to users than ever. We’re deploying more than twenty Runware Inference Pods across major cities in Europe and the US, delivering sub-10ms latency AI. And we’re extending Runware to support every model on Hugging Face, running them faster, cheaper, and more reliably than anyone else. A special thank you to Dawn Capital for leading this round, alongside Speedinvest Comcast Ventures Insight Partners a16z speedrun 🧊 Zero Prime VC Alex Menn at Begin Capital and all our early backers who supported us long before Runware looked like it does today.
0:48

Today we’re announcing our $50M Series A! Over the last year, we’ve grown from a small group with a big idea into a platform powering AI for hundreds of millions of end users across image, video, audio, and more. Since Q3, we’ve grown revenue by 10x, placing Runware comfortably among the fastest growing companies in the world. 🚀 When Runware started, the mission was simple: build the fastest and most reliable multimodal inference platform on the planet and make it accessible to everyone. We built our own Sonic Inference Engine, our own GPU infrastructure, our own inference pods, and a set of optimizations that push the limits of what an AI provider can do at scale. 2026 will be the year we bring inference closer to users than ever. We’re deploying more than twenty Runware Inference Pods across major cities in Europe and the US, delivering sub-10ms latency AI. And we’re extending Runware to support every model on Hugging Face, running them faster, cheaper, and more reliably than anyone else. A special thank you to Dawn Capital for leading this round, alongside Speedinvest Comcast Ventures Insight Partners a16z speedrun 🧊 Zero Prime VC Alex Menn at Begin Capital and all our early backers who supported us long before Runware looked like it does today.

Runware

63,604 görüntüleme • 8 ay önce

Chamath Palihapitiya just dropped the number that explains the entire AI infrastructure trade (Save this). A gigawatt of compute now costs $100 billion and when he started his Arizona data center project it was $4 to $5 billion, it has gone up 20x in a single investment cycle. The implication is not just that AI infrastructure is expensive but rather that the capital barrier to owning meaningful compute has become so high that only a handful of entities in the world can actually build it and the companies who got there early are sitting on what may be the most durable pricing power in the history of the technology industry. This is the neocloud trade. The neocloud market, purpose-built GPU cloud providers like CoreWeave, Nebius, and Lambda Labs was worth $35 billion in 2026 and is projected to reach $236 billion by 2031, compounding at 46% annually. For context, that is faster growth than cloud computing itself posted in its first decade. The reason is very simple, hyperscalers like AWS, Azure, and Google are building for everything, storage, databases, enterprise software, networking and their GPU pricing reflects the overhead of that full-stack infrastructure. Neoclouds build for one thing only, AI compute. The result is a 60% to 85% cost advantage on the same Nvidia silicon, bare metal H100s at $0.78 to $2.79 per GPU-hour on a neocloud versus $3.43 to $5.07 per GPU-hour on a hyperscaler. That spread does not close as AI demand scales but rather it widens, because hyperscalers have to amortize legacy infrastructure and margin expectations that neoclouds do not carry. Gartner projects that by 2030, neoclouds will capture 20% of the $267 billion AI cloud market, and Vultr's own analysis says at least 80% of GPU market share by end of 2026 will be held by a small group of scaled neocloud providers. Now zoom into Nebius specifically, because it is the most interesting publicly traded proxy for this trade. Nebius is the infrastructure arm of the former Yandex Russia's equivalent of Google rebuilt from the ground up after Russia's invasion of Ukraine by Arkady Volozh and relisted on Nasdaq in October 2024. The team that built it already knew how to run internet-scale infrastructure at the lowest possible cost, which is exactly the operational DNA a neocloud requires. In Q1 2026, Nebius reported revenue of $399 million and already generating serious cash on a young business with revenue growing nearly eightfold year-over-year. Then in March 2026, Meta signed a five-year infrastructure agreement with Nebius worth up to $27 billion, $12 billion in committed dedicated GPU capacity deployments beginning early 2027, plus up to $15 billion more tied to Meta purchasing Nebius's unsold third-party capacity. The deal will be executed on one of the first large-scale deployments of Nvidia's Vera Rubin platform, the next-generation architecture after Blackwell making Nebius one of a tiny number of operators in the world with confirmed priority access to the most advanced AI hardware available. Following the contract, Nebius guided to $7 to $9 billion in annualized recurring revenue for 2026 representing 540% year-over-year growth. Chamath Palihapitiya point about the $100 billion capital moat is the bear case for new entrants and the bull case for incumbents. No one can afford to build the next CoreWeave or Nebius from scratch at current hardware and power costs. The companies that are already built, already contracted, and already deploying Nvidia's latest silicon have a moat that compounds with every GPU generation cycle because they get allocations first, they deploy fastest, and their customers re-sign rather than wait for a new operator that does not yet exist. Come join Milk Road Pro for our full breakdown, the complete neocloud competitive landscape, how to think about Nebius's valuation versus CoreWeave and AI entire thesis. Link below.
0:20

Chamath Palihapitiya just dropped the number that explains the entire AI infrastructure trade (Save this). A gigawatt of compute now costs $100 billion and when he started his Arizona data center project it was $4 to $5 billion, it has gone up 20x in a single investment cycle. The implication is not just that AI infrastructure is expensive but rather that the capital barrier to owning meaningful compute has become so high that only a handful of entities in the world can actually build it and the companies who got there early are sitting on what may be the most durable pricing power in the history of the technology industry. This is the neocloud trade. The neocloud market, purpose-built GPU cloud providers like CoreWeave, Nebius, and Lambda Labs was worth $35 billion in 2026 and is projected to reach $236 billion by 2031, compounding at 46% annually. For context, that is faster growth than cloud computing itself posted in its first decade. The reason is very simple, hyperscalers like AWS, Azure, and Google are building for everything, storage, databases, enterprise software, networking and their GPU pricing reflects the overhead of that full-stack infrastructure. Neoclouds build for one thing only, AI compute. The result is a 60% to 85% cost advantage on the same Nvidia silicon, bare metal H100s at $0.78 to $2.79 per GPU-hour on a neocloud versus $3.43 to $5.07 per GPU-hour on a hyperscaler. That spread does not close as AI demand scales but rather it widens, because hyperscalers have to amortize legacy infrastructure and margin expectations that neoclouds do not carry. Gartner projects that by 2030, neoclouds will capture 20% of the $267 billion AI cloud market, and Vultr's own analysis says at least 80% of GPU market share by end of 2026 will be held by a small group of scaled neocloud providers. Now zoom into Nebius specifically, because it is the most interesting publicly traded proxy for this trade. Nebius is the infrastructure arm of the former Yandex Russia's equivalent of Google rebuilt from the ground up after Russia's invasion of Ukraine by Arkady Volozh and relisted on Nasdaq in October 2024. The team that built it already knew how to run internet-scale infrastructure at the lowest possible cost, which is exactly the operational DNA a neocloud requires. In Q1 2026, Nebius reported revenue of $399 million and already generating serious cash on a young business with revenue growing nearly eightfold year-over-year. Then in March 2026, Meta signed a five-year infrastructure agreement with Nebius worth up to $27 billion, $12 billion in committed dedicated GPU capacity deployments beginning early 2027, plus up to $15 billion more tied to Meta purchasing Nebius's unsold third-party capacity. The deal will be executed on one of the first large-scale deployments of Nvidia's Vera Rubin platform, the next-generation architecture after Blackwell making Nebius one of a tiny number of operators in the world with confirmed priority access to the most advanced AI hardware available. Following the contract, Nebius guided to $7 to $9 billion in annualized recurring revenue for 2026 representing 540% year-over-year growth. Chamath Palihapitiya point about the $100 billion capital moat is the bear case for new entrants and the bull case for incumbents. No one can afford to build the next CoreWeave or Nebius from scratch at current hardware and power costs. The companies that are already built, already contracted, and already deploying Nvidia's latest silicon have a moat that compounds with every GPU generation cycle because they get allocations first, they deploy fastest, and their customers re-sign rather than wait for a new operator that does not yet exist. Come join Milk Road Pro for our full breakdown, the complete neocloud competitive landscape, how to think about Nebius's valuation versus CoreWeave and AI entire thesis. Link below.

Milk Road AI

139,047 görüntüleme • 2 ay önce

🚀 Here’s more on AgentCore, launched today: If AI agents are going to transform how we work and live, developers need the right set of tools to move them from prototype to production at scale. Today, I'm thrilled to announce Amazon Bedrock AgentCore, a comprehensive set of services to deploy and operate highly capable agents securely at scale. The journey from prototype to production for AI agents has been filled with complex infrastructure challenges. Teams spend months building secure runtime environments, implementing memory systems, and creating monitoring solutions. AgentCore eliminates this undifferentiated heavy lifting, with fully-managed, modular services - providing everything you need to operate trustworthy agents. What makes AgentCore powerful: 🟠 Complete Development Flexibility: Build agents your way using any framework and any model, and work with any protocol (including MCP and A2A) - all while maintaining enterprise-grade security and control 🟠 Purpose-Built Infrastructure: First serverless runtime to offer framework-agnostic flexibility, complete session isolation, and industry-leading 8-hour workload support 🟠 Trust and Reliability: Built on AWS's proven security foundation with built-in identity controls and strict security boundaries for operating agents at scale 🟠 Composable Services: Use exactly what you need independently or together, paying only for what you use as your needs evolve AgentCore represents a significant milestone in our mission to make advanced AI accessible and practical for every organization. Whether you're just starting with AI agents or scaling enterprise-wide implementations, AgentCore gives you the foundation to build with confidence. This is just the beginning of our journey to enable an agentic future. Can't wait to see the transformative solutions you'll build with AgentCore! Bring your AI agents to life at scale – learn more about AgentCore today. Amazon Web Services #AmazonBedrock #AgentCore
1:29

🚀 Here’s more on AgentCore, launched today: If AI agents are going to transform how we work and live, developers need the right set of tools to move them from prototype to production at scale. Today, I'm thrilled to announce Amazon Bedrock AgentCore, a comprehensive set of services to deploy and operate highly capable agents securely at scale. The journey from prototype to production for AI agents has been filled with complex infrastructure challenges. Teams spend months building secure runtime environments, implementing memory systems, and creating monitoring solutions. AgentCore eliminates this undifferentiated heavy lifting, with fully-managed, modular services - providing everything you need to operate trustworthy agents. What makes AgentCore powerful: 🟠 Complete Development Flexibility: Build agents your way using any framework and any model, and work with any protocol (including MCP and A2A) - all while maintaining enterprise-grade security and control 🟠 Purpose-Built Infrastructure: First serverless runtime to offer framework-agnostic flexibility, complete session isolation, and industry-leading 8-hour workload support 🟠 Trust and Reliability: Built on AWS's proven security foundation with built-in identity controls and strict security boundaries for operating agents at scale 🟠 Composable Services: Use exactly what you need independently or together, paying only for what you use as your needs evolve AgentCore represents a significant milestone in our mission to make advanced AI accessible and practical for every organization. Whether you're just starting with AI agents or scaling enterprise-wide implementations, AgentCore gives you the foundation to build with confidence. This is just the beginning of our journey to enable an agentic future. Can't wait to see the transformative solutions you'll build with AgentCore! Bring your AI agents to life at scale – learn more about AgentCore today. Amazon Web Services #AmazonBedrock #AgentCore

Swami Sivasubramanian

11,646 görüntüleme • 1 yıl önce

Nebius is one of the most undervalued AI infrastructure companies in the public markets right now (Save this). Leopold Aschenbrenner, the former OpenAI researcher who wrote the 165-page essay predicting AGI within this decade and then launched the $13.7 billion Situational Awareness Fund around that thesis just filed a 13G disclosing a 5.6% stake in Nebius, representing 12.41 million Class A shares. This is the man whose entire investment framework is built on one core conviction, AI will advance faster than anyone expects, and the binding constraint will not be algorithms or model architectures, it will be physical computing infrastructure, data center capacity, and energy. Now look at what Nebius actually is and why this conviction is justified by the numbers alone. Nebius is a GPU native AI cloud platform, a neocloud built from the ground up specifically for AI training and inference workloads, founded by Arkady Volozh, the former CEO of Yandex who divested all non-Russian assets and left Russia in direct opposition to Putin before relisting the company on Nasdaq. In Q1 2026, Nebius reported $399 million in revenue, a 684% increase year over year from just $50.9 million while also delivering EBITDA and adjusted EPS that beat consensus estimates by 43% and 50% respectively, in a quarter where analysts had already built in aggressive assumptions. The scale of the infrastructure buildout is what makes the valuation argument so compelling. Nebius has raised its contracted power capacity guidance to over 4 gigawatts for 2026, with a target of 5 gigawatts of AI computing capacity deployed by 2030, including multiple gigawatt-scale AI factories across the United States and Europe. The Finland campus coming soon to Lappeenranta will be 310 megawatts powered by low-carbon energy, making it one of the largest AI data centers in Europe, specifically located in a cold-climate, energy-stable region that dramatically reduces cooling costs and carbon intensity. The 2026 capacity is already effectively sold out according to management disclosures, which means every megawatt Nebius brings online has a revenue contract attached to it before the facility opens. The strategic backing validates the thesis at every level. NVIDIA committed a $2 billion strategic investment in Nebius by 2030, with the two companies co-developing an inference stack, implementing NVIDIA's GPU health monitoring systems, and deploying next-generation architectures including Rubin GPUs, Vera CPUs, and Bluefield storage systems meaning Nebius gets preferential access to the hardware that every other AI company is begging Jensen Huang for. Meta signed a $27 billion agreement with Nebius, with $12 billion in dedicated computing resources confirmed and up to $15 billion in additional capacity over the coming years. And Nebius just partnered with Bloom Energy on a $2.6 billion deal guaranteeing 328 megawatts of installed capacity through modular fuel cell systems behind the meter power that eliminates grid dependency and accelerates deployment timelines. The forward valuation math is where the undervaluation case becomes undeniable. Nebius is pricing in $3.5 billion in revenue for 2026 and $11 billion for 2027, which puts the forward price-to-sales ratio at 16.6 times for this year and just 5.3 times for next year for a company growing revenue at 684% year over year with sold out capacity, NVIDIA backing, a $27 billion Meta contract, and a path to 4+ gigawatts of contracted power. Milk Road has been positioned in Nebius and we believe the convergence of Leopold's conviction stake, NVIDIA's $2 billion endorsement, Meta's $27 billion commitment, and a physical infrastructure buildout that is sold out before it opens represents one of the highest-quality risk-reward setups in AI infrastructure today. Come join Milk Road Pro and get our full Nebius thesis including the exact framework we use to think about neocloud valuation, the power capacity math that determines when revenue accelerates, and every catalyst we are watching through 2027. Link in bio/below.
0:20

Nebius is one of the most undervalued AI infrastructure companies in the public markets right now (Save this). Leopold Aschenbrenner, the former OpenAI researcher who wrote the 165-page essay predicting AGI within this decade and then launched the $13.7 billion Situational Awareness Fund around that thesis just filed a 13G disclosing a 5.6% stake in Nebius, representing 12.41 million Class A shares. This is the man whose entire investment framework is built on one core conviction, AI will advance faster than anyone expects, and the binding constraint will not be algorithms or model architectures, it will be physical computing infrastructure, data center capacity, and energy. Now look at what Nebius actually is and why this conviction is justified by the numbers alone. Nebius is a GPU native AI cloud platform, a neocloud built from the ground up specifically for AI training and inference workloads, founded by Arkady Volozh, the former CEO of Yandex who divested all non-Russian assets and left Russia in direct opposition to Putin before relisting the company on Nasdaq. In Q1 2026, Nebius reported $399 million in revenue, a 684% increase year over year from just $50.9 million while also delivering EBITDA and adjusted EPS that beat consensus estimates by 43% and 50% respectively, in a quarter where analysts had already built in aggressive assumptions. The scale of the infrastructure buildout is what makes the valuation argument so compelling. Nebius has raised its contracted power capacity guidance to over 4 gigawatts for 2026, with a target of 5 gigawatts of AI computing capacity deployed by 2030, including multiple gigawatt-scale AI factories across the United States and Europe. The Finland campus coming soon to Lappeenranta will be 310 megawatts powered by low-carbon energy, making it one of the largest AI data centers in Europe, specifically located in a cold-climate, energy-stable region that dramatically reduces cooling costs and carbon intensity. The 2026 capacity is already effectively sold out according to management disclosures, which means every megawatt Nebius brings online has a revenue contract attached to it before the facility opens. The strategic backing validates the thesis at every level. NVIDIA committed a $2 billion strategic investment in Nebius by 2030, with the two companies co-developing an inference stack, implementing NVIDIA's GPU health monitoring systems, and deploying next-generation architectures including Rubin GPUs, Vera CPUs, and Bluefield storage systems meaning Nebius gets preferential access to the hardware that every other AI company is begging Jensen Huang for. Meta signed a $27 billion agreement with Nebius, with $12 billion in dedicated computing resources confirmed and up to $15 billion in additional capacity over the coming years. And Nebius just partnered with Bloom Energy on a $2.6 billion deal guaranteeing 328 megawatts of installed capacity through modular fuel cell systems behind the meter power that eliminates grid dependency and accelerates deployment timelines. The forward valuation math is where the undervaluation case becomes undeniable. Nebius is pricing in $3.5 billion in revenue for 2026 and $11 billion for 2027, which puts the forward price-to-sales ratio at 16.6 times for this year and just 5.3 times for next year for a company growing revenue at 684% year over year with sold out capacity, NVIDIA backing, a $27 billion Meta contract, and a path to 4+ gigawatts of contracted power. Milk Road has been positioned in Nebius and we believe the convergence of Leopold's conviction stake, NVIDIA's $2 billion endorsement, Meta's $27 billion commitment, and a physical infrastructure buildout that is sold out before it opens represents one of the highest-quality risk-reward setups in AI infrastructure today. Come join Milk Road Pro and get our full Nebius thesis including the exact framework we use to think about neocloud valuation, the power capacity math that determines when revenue accelerates, and every catalyst we are watching through 2027. Link in bio/below.

Milk Road AI

61,932 görüntüleme • 3 ay önce

I’m excited to share that we’ve raised a $70M Series B, led by a16z and ICONIQ - bringing our total funding to over $100M in under a year. Accounting is a $500B category, and yet most finance teams are still running on systems built in the 90s. Rillet is rebuilding the financial core of modern companies. We’ve rebuilt the general ledger from the ground up to assemble the first AI-native ERP, built for speed, flexibility, and automation. Since coming out of stealth ~12 months ago, we’ve grown lightning fast. We now power the finance stack behind companies like Postscript, Windsurf (retired), Decagon, Bitwarden and many more across many industries. Windsurf scaled revenue 10x while running global finance with just two people and Rillet. Postscript, with over $100M in ARR and four entities, now closes their books in three days. These are the kinds of results we hold ourselves to. We’ve also partnered with some of the largest and best accounting firms in the country, including Armanino, Wiss Labs and Attivo. The whole industry has been begging for change for decades. With Rillet, it’s here. This round came together very quickly. The first call happened while I was eating a tuna sandwich in SF (I did not finish it). Three days later, we had a signed term sheet. It was a reflection of the momentum we’re seeing both in the product and in the market. Since announcing our Series A just weeks ago, we’ve already doubled our ARR. None of this would be possible without our team of accountants and engineers. A few months ago, I was still jumping on support calls to help customers. Today, our implementation, success, and product teams are delivering outcomes with the same speed and care that got us here. We originally booked an offsite to celebrate the Series A. In classic Rillet speed fashion, it’s now an A + B celebration. It’s proof of how fast things can move when customers love the product and a reminder of how much this team has earned the chance to celebrate together. We’re fortunate to welcome a16z and ICONIQ to the table. Alex Rampell, Seema Amble, Marc Andrusko and Seth Pierrepont, Sarah bring clarity, urgency and deep conviction about the future of AI and finance. We’re also grateful to have continued support from our early partners Sequoia Capital, First Round, Creandum who believed in us from the start, and excited about working with Oak HC/FT and FOG Ventures. To the Rillet team, again - thank you for building with care, focus, and speed. To our customers - thank you for pushing us, trusting us, and helping shape the product. We are honored to serve you. Let’s go!
1:58

I’m excited to share that we’ve raised a $70M Series B, led by a16z and ICONIQ - bringing our total funding to over $100M in under a year. Accounting is a $500B category, and yet most finance teams are still running on systems built in the 90s. Rillet is rebuilding the financial core of modern companies. We’ve rebuilt the general ledger from the ground up to assemble the first AI-native ERP, built for speed, flexibility, and automation. Since coming out of stealth ~12 months ago, we’ve grown lightning fast. We now power the finance stack behind companies like Postscript, Windsurf (retired), Decagon, Bitwarden and many more across many industries. Windsurf scaled revenue 10x while running global finance with just two people and Rillet. Postscript, with over $100M in ARR and four entities, now closes their books in three days. These are the kinds of results we hold ourselves to. We’ve also partnered with some of the largest and best accounting firms in the country, including Armanino, Wiss Labs and Attivo. The whole industry has been begging for change for decades. With Rillet, it’s here. This round came together very quickly. The first call happened while I was eating a tuna sandwich in SF (I did not finish it). Three days later, we had a signed term sheet. It was a reflection of the momentum we’re seeing both in the product and in the market. Since announcing our Series A just weeks ago, we’ve already doubled our ARR. None of this would be possible without our team of accountants and engineers. A few months ago, I was still jumping on support calls to help customers. Today, our implementation, success, and product teams are delivering outcomes with the same speed and care that got us here. We originally booked an offsite to celebrate the Series A. In classic Rillet speed fashion, it’s now an A + B celebration. It’s proof of how fast things can move when customers love the product and a reminder of how much this team has earned the chance to celebrate together. We’re fortunate to welcome a16z and ICONIQ to the table. Alex Rampell, Seema Amble, Marc Andrusko and Seth Pierrepont, Sarah bring clarity, urgency and deep conviction about the future of AI and finance. We’re also grateful to have continued support from our early partners Sequoia Capital, First Round, Creandum who believed in us from the start, and excited about working with Oak HC/FT and FOG Ventures. To the Rillet team, again - thank you for building with care, focus, and speed. To our customers - thank you for pushing us, trusting us, and helping shape the product. We are honored to serve you. Let’s go!

Nicolas Kopp

257,874 görüntüleme • 1 yıl önce

Today, we’re excited to announce our $50M Series B, led by Greenfield Partners (formerly TPG Capital), with participation from Lightspeed and Notable Capital. 🚀 At PatronusAI, we develop simulations and evals to train and improve AI. The first phase of AI was built on static benchmarks, but that era is over now. As agents are used to solve longer and longer tasks, they need to practice in dynamic, living worlds to get better. Simulations are the critical infrastructure powering this next phase. As a company, we’re behind the most influential research and products in AI evaluation, like FinanceBench, Lynx, and Percival. And things have moved at the speed of light since. ⚡ We partner with the world's leading frontier AI labs and enterprises, and our revenue has grown more than 15x over the past year. Additionally, today, we’re introducing a preview of the first Digital World Model for AI agent training and simulation: Patronus-DWM. Digital World Models are language diffusion world models that predict realistic environment behaviors and steer agent actions across digital workflows. Just as physical world models predict how objects move through space, we’re developing the equivalent for the digital world: predicting how agents act in digital workflows, then using that to scale the creation of high-quality training data for LLMs. Digital World Models help us push the frontier of ultra long horizon workflows, and unlock a new class of self-improving RL environments. This is our scalable approach to simulating all of the world’s intelligence. The round was also joined by Datadog, Inc., Samsung Ventures, Gokul Rajaram, Factorial Capital, and a large cohort of amazing AI leaders and researchers across Anthropic, OpenAI, Google DeepMind, NVIDIA, Recursive, and more. ✨ It has been the ride of a lifetime. But we’re just getting started. The best is yet to come. "Do not go gentle into that good night, Rage, rage against the dying of the light" - Dylan Thomas (1954)
1:50

Today, we’re excited to announce our $50M Series B, led by Greenfield Partners (formerly TPG Capital), with participation from Lightspeed and Notable Capital. 🚀 At PatronusAI, we develop simulations and evals to train and improve AI. The first phase of AI was built on static benchmarks, but that era is over now. As agents are used to solve longer and longer tasks, they need to practice in dynamic, living worlds to get better. Simulations are the critical infrastructure powering this next phase. As a company, we’re behind the most influential research and products in AI evaluation, like FinanceBench, Lynx, and Percival. And things have moved at the speed of light since. ⚡ We partner with the world's leading frontier AI labs and enterprises, and our revenue has grown more than 15x over the past year. Additionally, today, we’re introducing a preview of the first Digital World Model for AI agent training and simulation: Patronus-DWM. Digital World Models are language diffusion world models that predict realistic environment behaviors and steer agent actions across digital workflows. Just as physical world models predict how objects move through space, we’re developing the equivalent for the digital world: predicting how agents act in digital workflows, then using that to scale the creation of high-quality training data for LLMs. Digital World Models help us push the frontier of ultra long horizon workflows, and unlock a new class of self-improving RL environments. This is our scalable approach to simulating all of the world’s intelligence. The round was also joined by Datadog, Inc., Samsung Ventures, Gokul Rajaram, Factorial Capital, and a large cohort of amazing AI leaders and researchers across Anthropic, OpenAI, Google DeepMind, NVIDIA, Recursive, and more. ✨ It has been the ride of a lifetime. But we’re just getting started. The best is yet to come. "Do not go gentle into that good night, Rage, rage against the dying of the light" - Dylan Thomas (1954)

Anand Kannappan

42,134 görüntüleme • 2 ay önce

Today, we’re excited to announce our $50M Series B, led by Greenfield Partners, with participation from Lightspeed and Notable Capital. 🚀 At Patronus AI, we develop simulations and evals to train and improve AI. The first phase of AI was built on static benchmarks, but that era is over. As agents are used to solve longer and longer tasks, they need to practice in dynamic, living worlds to get better. Simulations are the critical infrastructure powering this next phase. As a company, we’re behind the most influential research and products in AI evaluation, like FinanceBench, Lynx, and Percival. And things have moved at the speed of light since.⚡ We partner with the world's leading frontier AI labs and enterprises, and our revenue has grown more than 15x over the past year. Additionally, today, we’re introducing a preview of the first Digital World Model for AI agent training and simulation: Patronus-DWM. Digital World Models are language diffusion world models that predict realistic environment behaviors and steer agent actions across digital workflows. Just as physical world models predict how objects move through space, we’re developing the equivalent for the digital world: predicting how agents act in digital workflows, then using that to scale the creation of high-quality training data for LLMs. Digital World Models help us push the frontier of ultra long horizon workflows, and unlock a new class of self-improving RL environments. This is our scalable approach to simulating all of the world’s intelligence. The round was also joined by Datadog, Inc., Samsung Ventures, Gokul Rajaram, Factorial Capital, and a large cohort of amazing AI leaders across Anthropic, OpenAI, Google DeepMind, NVIDIA, Recursive, and more.✨ It has been the ride of a lifetime. But we’re just getting started. The best is yet to come. "Do not go gentle into that good night, Rage, rage against the dying of the light" - Dylan Thomas (1954)
1:50

Today, we’re excited to announce our $50M Series B, led by Greenfield Partners, with participation from Lightspeed and Notable Capital. 🚀 At Patronus AI, we develop simulations and evals to train and improve AI. The first phase of AI was built on static benchmarks, but that era is over. As agents are used to solve longer and longer tasks, they need to practice in dynamic, living worlds to get better. Simulations are the critical infrastructure powering this next phase. As a company, we’re behind the most influential research and products in AI evaluation, like FinanceBench, Lynx, and Percival. And things have moved at the speed of light since.⚡ We partner with the world's leading frontier AI labs and enterprises, and our revenue has grown more than 15x over the past year. Additionally, today, we’re introducing a preview of the first Digital World Model for AI agent training and simulation: Patronus-DWM. Digital World Models are language diffusion world models that predict realistic environment behaviors and steer agent actions across digital workflows. Just as physical world models predict how objects move through space, we’re developing the equivalent for the digital world: predicting how agents act in digital workflows, then using that to scale the creation of high-quality training data for LLMs. Digital World Models help us push the frontier of ultra long horizon workflows, and unlock a new class of self-improving RL environments. This is our scalable approach to simulating all of the world’s intelligence. The round was also joined by Datadog, Inc., Samsung Ventures, Gokul Rajaram, Factorial Capital, and a large cohort of amazing AI leaders across Anthropic, OpenAI, Google DeepMind, NVIDIA, Recursive, and more.✨ It has been the ride of a lifetime. But we’re just getting started. The best is yet to come. "Do not go gentle into that good night, Rage, rage against the dying of the light" - Dylan Thomas (1954)

PatronusAI

95,248 görüntüleme • 2 ay önce